Increasing networking and growing data volumes in manufacturing companies open up new challenges and opportunities for process optimization. The greatest optimization potential lies in the insights that can be gained from the relationships between the data. However, due to the sheer volume as well as the complex relationships between the available data, classical analysis methods are reaching their limits. The group Process Insights therefore conduct research into new approaches and methods in the field of data analysis - such as machine learning - in order to identify deviations and errors in the process at an early stage or to avoid them accordingly.
Within the framework of the research project, a smart service platform is being developed, which enables and supports the digitalization process in SMEs by providing various services („Apps“). Based on digitally stored data, production processes are being analyzed, planned, controlled and their future behaviour is being projected.
KoSyF - Collaborative-Synchronized Manufacturing
The overall objectives of the research project are to strengthen the integration of employees in production planning and control of individual and small-batch production, as well as the development of corresponding technical support systems. In addition to new forms of organization - in conjunction with interactive management systems - the paperless production as well as order location via BLE beacons are the focus of the project.
The research project ProFAP deals with the optimization of production-related error-abatement processes in the German machine tools industry. The objective is to develop a tool for the analysis and continuous improvement of these processes in small and medium-sized enterprises.
The research project MoFaPro deals with the optimization of production-related error-abatement processes in manufacturing enterprises. The objective is the derivation of recommendations for an effective and efficient integration of the error-abatement process into the production process by means of a system-dynamic simulation model.
The research project SMoPa3D deals with the development of a sensor system as well as a thereon based model-based control for real-time monitoring of several target variables of additive production processes.
In the research project KMU Move we are working on the development of a system for the migration of normative management systems, using the example of the current revision of ISO 9001. The results are implemented in an interactive wiki tool.
The aim of the research project is the formulation of general rules for cost-efficient design of process and test sequences by systematically explaining the complex causalities between the manufacturing history and the inspection decision by means of an analytical model.
SynErgie - Quality Management for Energy-Synchronous Production
Within the scope of the research project, quality management methods are supplemented or developed in such a way that a consistently high product and process quality is ensured despite process interruptions due to energy-adaptive production. For this purpose, first of all, research is carried out on which systems or during which phases a process interruption is critical or uncritical. After that, existing quality management methods are adapted for the necessary interruption during the critical process phases (e.g. by statistical process control) or replaced by new methods.